Johannes Bulin: Large-scale time parallelization for molecular dynamics problems

As modern supercomputers draw their power from the sheer number of cores, an efficient parallelization of programs is crucial for achieving good performance. When one tries to solve differential equations in parallel this is usually done by parallelizing the computation of one single time step. As the speedup of such parallelization schemes is usually limited, e.g. by the spatial size of the problem, additional parallelization in time may be useful to achieve better scalability.

This thesis will introduce two well-known schemes for time-parallelization, namely the waveform relaxation method and the parareal algorithm. These methods are then applied to a molecular dynamics problem which is a useful test example as the number of required time steps is high while the number of unknowns is relatively low. Afterwards it is investigated how these methods can be adapted to large-scale computations.